thu-ml/zhusuan

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2219 stars · 413 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

ZhuSuan is a Python probabilistic programming library for Bayesian deep learning built on TensorFlow. It provides primitives for building probabilistic models and inference algorithms such as variational inference, importance sampling, and MCMC methods.

Use cases

• build Bayesian neural networks with variational inference
• train deep generative models like VAEs
• run Hamiltonian Monte Carlo on probabilistic models
• apply stochastic gradient MCMC to deep learning models
• evaluate generative models with importance sampling
• prototype hierarchical Bayesian models

When to choose

• you need Bayesian inference combined with deep learning in TensorFlow
• you want advanced gradient estimators like VIMCO or REINFORCE
• you need programmable variational posteriors or importance sampling proposals

When to avoid

• you work with PyTorch or JAX instead of TensorFlow
• you need a library with frequent updates and active community support
• you only need standard supervised deep learning without probabilistic modeling

Facets

library · maturity maintenance

machine-learning deep-learning simulation machine-learning deep-learning artificial-intelligence python probabilistic-programming bayesian-inference generative-models tensorflow variational-inference mcmc

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